Field of the Invention
The present invention relates to a method for determining an exposure of a structured light-based 3D camera.
Description of the Related Art
Generally, technologies for reconstructing a 3D image of an object using one or more cameras may be largely classified as either being active or passive techniques. Examples of active techniques include laser triangulation and structured light. An example of a passive technique is stereovision. Active techniques are typically preferred for research or industrial purposes because they may achieve higher precision scanning than passive techniques.
A 3D camera system for use with structured light can be considered as a modification of a stereo camera system. In particular, unlike a stereo camera system, in which two identical cameras are used, a 3D camera system used for structured light is configured such that one camera is replaced by a projection device such, as a beam projector. Accordingly, in a 3D camera system used for structured light scanning, one or more patterns are projected onto an object using a projection device, an image of the object onto which the pattern is projected is captured using an image-capturing device, such as a camera, and 3D information about the object is acquired by analyzing the captured image.
In other words, because a stereo camera system passively uses features extracted from an image but a structured light-based camera system actively projects one or more patterns onto an object using a projection device and uses the projected pattern to distinguish features of the object, a structured light-based camera system has a fast processing speed and high spatial resolution. Thanks to these advantages, the structured light-based camera system is widely used in various fields, such as object modeling and recognition, 3D measurement, industrial inspection, reverse engineering, and the like.
However, structured light-based camera systems have the following general problems.
Generally, in the real world, objects have various reflection coefficients. Accordingly, when patterns are projected from a projection device onto an object having a low reflection coefficient (for example, a black ball), it is difficult to correctly acquire the projected patterns using a capturing device. Conversely, when patterns are projected onto an object having a high reflection coefficient (for example, a white ball having a glossy surface), because the gloss causes saturation of patterns (seen as blurred patterns) in the image acquired using a capturing device, it is difficult to acquire accurate patterns. Also, light conditions of a real environment may affect the image acquisition of patterns. Additionally, it may be difficult to acquire accurate patterns in a real environment that is too bright or too dark.